Efficacy of a pressure-sensing mattress cover system for reducing interface pressure: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Interface pressure is a key risk factor in the development of pressure ulcers. Visual feedback of continuous interface pressure between the body and support surface could inform clinicians on repositioning strategies and play a key role in an overall strategy for the prevention and management of pressure ulcers. METHODS/DESIGN: A parallel two-group randomized controlled clinical trial will be conducted to study the effect of continuous pressure imaging on reducing interface pressure and on the incidence of pressure ulcers in vulnerable hospital patients. A total of 678 eligible consenting inpatients at risk of pressure ulcer development in a tertiary acute care institution will be randomly allocated to either having the ForeSite PT™ system with the liquid-crystal display monitor turned on to provide visual feedback to the clinicians while also collecting continuous interface pressure data (intervention group) or to having the ForeSite PT™ system with monitor turned off (that is, not providing visual feedback) but still collecting continuous interface pressure data (control group), in a ratio of 1:1. Continuous interface pressure data will be collected in both groups for 3 days (72 h). Data collection will continue until discharge for a subset of approximately 60 patients. The primary outcome will be the differences in the two groups' interface pressure analysis. Interface pressure readings will be collected through hourly samplings of continuous interface pressure recordings. Secondary outcomes will be the differences between the two groups in pressure-related skin and soft tissue changes in areas at risk of pressure ulcer (obtained at baseline within 24 h of admission) and on the third day of the trial or at discharge and perceptions of the intervention by patients and clinicians (obtained on the third day or at discharge). DISCUSSION: This will be the first randomized controlled trial to investigate the effect of visual feedback with continuous interface pressure of vulnerable hospital patients across different care settings, and the association between interface pressure and development of pressure-related skin and soft tissue changes. The results could provide important information to guide clinical practice in the prevention and management of pressure ulcers. TRIALS REGISTRATION: ClinicalTrials.gov NCT02325388 (date of registration: 24 December 2014).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.031 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.063 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".